1. Field of the Invention
The present invention relates to a speech coding system, more particularly to a speech coding system which performs a high quality compression of speech information signals using a vector quantization technique.
Recently in, for example, intra-company communication systems and digital mobile radio communication systems, a vector quantization method of compressing speech information signals while maintaining the speech quality is employed. According to the vector quantization method, first a reproduced signal is obtained by applying a prediction weighting to each signal vector in a codebook, and then an error power between the reproduced signal and an input speech signal is evaluated to determine a number, i.e., index, of the signal vector which provides a minimum error power. Nevertheless a more advanced vector quantization method is now needed to realize a greater compression of the speech information.
2. Description of the Related Art
A well known typical high quality speech coding method is a code-excited linear prediction (CELP) coding method, which uses the aforesaid vector quantization. The conventional CELP coding is known as sequential optimization CELP coding or simultaneous optimization CELP coding. These typical CELP codings will be explained in detail hereinafter.
As will be understood later, a gain (b) optimization for each vector of an adaptive codebook and a gain (g) optimization for each vector of a stochastic codebook are carried out sequentially and independently under the sequential optimization CELP coding, and are carried out simultaneously under the simultaneous optimization CELP coding.
The simultaneous optimization CELP is superior to the sequential optimization CELP coding from the view point of the realization of high quality speech reproduction, but the simultaneous optimization CELP coding has a drawback in that the computation amount becomes larger than that of the sequential optimization CELP coding.
Namely, the problem with the CELP coding lies in the massive amount of digital calculations required for encoding speech, which makes it extremely difficult to conduct speech communication in real time. Theoretically, the realization of such a speech coding apparatus enabling real time speech communication is possible, but a supercomputer would be required for the above digital calculations, and accordingly in practice it would be impossible to obtain compact (handy type) speech coding apparatus.
To overcome this problems, the use of a sparse-stochastic codebook which stores therein, as white noise, a plurality of thinned out code vectors has been proposed, and this effectively reduces the calculation amount.